Introduction National essential medicines lists (NEMLs) guide medicine selection and procurement and are key tools for ...

Objective SLE is a heterogeneous systemic autoimmune disease with diverse clinical manifestations. We aimed to identify ...

Abstract: Fairness in clustering has recently received significant attention. The goal of fair clustering is to ensure that a clustering algorithm mitigates or even eliminates bias in the original ...

Graclus (latest: Version 1.2) is a fast graph clustering software that computes normalized cut and ratio association for a given undirected graph without any eigenvector computation. This is possible ...

Department of Chemistry, University of Florida, Gainesville, Florida 32611, United States Quantum Theory Project, University of Florida, Gainesville, Florida 32611, United States Laufer Center for ...

Data clustering is the process of grouping data items so that similar items are placed in the same cluster. There are several different clustering techniques, and each technique has many variations.

Abstract: K-means clustering algorithm is one of the most popular technique for clustering in machine learning, however, in the existing k-means clustering algorithm, the ability of the different ...

1 Department of Communication Science and Engineering, Nelson Mandela Institution of Science and Technology, Arusha, Tanzania. 2 School for Information Sciences, Center for Information and Systems, ...

Correspondence to Dr Diana Bonderman, Department of Internal Medicine II, Medical University of Vienna, Wien, Austria; diana.bonderman{at}meduniwien.ac.at Background Diagnosis of cardiac amyloidosis ...

Though we’re living through a time of extraordinary innovation in GPU-accelerated machine learning, the latest research papers frequently (and prominently) feature algorithms that are decades, in ...